Title:	Identificação de solo exposto e cupinzeiros em pastagens utilizando deep learning.
Authors:	ALMEIDA, I. P. FERNANDES, A. PARREIRA, W. D. OLIVEIRA, M. F. de GUCKERT, K. S. COELHO, D. K.
Affiliation:	IAN PINTO ALMEIDA, UNIVERSIDADE DO VALE DO ITAJAÍ; ANITA FERNANDES, UNIVERSIDADE DO VALE DO ITAJAÍ; WEMERSON DELCIO PARREIRA, PUC-CAMPINAS; MAURILIO FERNANDES DE OLIVEIRA, CNPMS; KAROLINE SOUZA GUCKERT, UNIVERSIDADE DO VALE DO ITAJAÍ; DENNIS KERR COELHO, UNIVERSIDADE DO VALE DO ITAJAÍ.
Date Issued:	2024
Citation:	In: COMPUTER ON THE BEACH, 15., 2024, Balneário Camburiú. Anais... São José: Universidade do Vale do Itajaí, 2024.
Description:	Pasture degradation is a significant challenge in livestock farming in Brazil, affecting the environmental and economic sustainability of the sector. Solutions that help manage pasture areas are crucial for Brazilian agribusiness. In this context, this work presents the application of YOLO model of Deep Learning to identify exposed soil, as well as indicators of pasture degradation, in this case, the number of termite mounds in each area. The image base used refers to pastures in Goiás and Mato Grosso.
Thesagro:	Pastagem Cupim
NAL Thesaurus:	Degradation Pastures
Keywords:	Degradação de pastagem Modelo YOLO Deep Learning
Type of Material:	Artigo em anais e proceedings
Access:	openAccess
Appears in Collections:	Artigo em anais de congresso (CNPMS)